License Plate Recognition (LPR) systems are typically employed to scan and log license plate information associated with vehicles parked in publically accessible areas. A typical LPR unit performs image analysis on captured images to identify the license plate number associated with each image. A typical LPR unit generates a record for each license plate number captured. The record may include any of an optical character recognition (OCR) interpretation of the captured license plate image (e.g., output in text string object format), images of the license plate number, a perspective image of the vehicle associated with the license plate number, the date and time of image capture, and the location of the LPR unit at the time of image capture. By continuing to operate each LPR unit for prolonged periods of time over a large area, the amount of aggregated license plate identification information grows. In addition, by combining the information generated by many LPR units, an LPR system may develop a large record of LPR information.
A large record of LPR information is useable for a variety of purposes. In one example, the location of a stolen vehicle may be identified based on a database of LPR information by searching the database for instances that match the license plate number of the stolen vehicle. Based on the time and location information that matches this license plate number, law enforcement officials may be able to locate the vehicle without costly investigation.
However, it may also be useful to predict the location of a person of interest using LPR information. Current methods of prioritizing investigative work aimed at locating persons of interest are based on simple metrics (e.g., credit score or recent update of public address record). Consequently, investigative efforts are often misallocated resulting in inefficiency. Thus, improvements are desired to assist in the prioritization of investigative work associated with locating persons of interest based on LPR information.